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Tunnel Pulse with Quiet Boundaries

A pressure pulse is being applied to the tunnel boundary with a frequency of 4 Hz over tens of milliseconds. Quiet (i.e., viscous) boundaries have been applied to all but the top of the model, which remains a free surface.

An Introduction to Python Scripting: Part 3

Introduction to Python scripting by reviewing key concepts and through demonstrations. Part 3 focuses on modules and packages, with a focus on NumPy and Matplotlib.

FLAC3D 7 0 Octree Mesh Tutorial

In this example, a pile of earth is modeled overlying undulating ground. This tutorial demonstrates how a FLAC3D model mesh can be easily created using DXF geometries and the ZONE DENSIFY command. How to differentiate parts of the model into separate GROUPs using DXF geometries and the GEOMETRY-SPACE range logic is also demonstrated.

Artiklar och presentationer

A Discrete Fracture Network Model With Stress-Driven Nucleation: Impact on Clustering, Connectivity, and Topology

The realism of Discrete Fracture Network (DFN) models relies on the spatial organization of fractures, which is not issued by purely stochastic DFN models. In this study, we introduce correlations between fractures by enhancing the genetic model (UFM) of Davy et al. [1] based on simplified concepts of nucleation, growth and arrest with hierarchical rules.

Three-dimensional Modeling and Stress Calibration for a Complex Mining Geometry

Study stress situation for potential continued mining towards greater depths; stress calibration against stress measurements using numerical modeling; and use of calibrated model to study stresses at existing infrastructure, study stresses at potential future haulage level locations, and as input to local models.

Blast Movement Simulation Through a Hybrid Approach of Continuum, Discontinuum, and Machine Learning Modeling

This work presents a hybrid modeling approach to efficiently estimate and optimize rock movement during blasting. A small-scale continuum model simulates early-stage, near-field blasting physics and generates synthetic data to train a machine learning (ML) model. Key parameters such as expanded hole diameter, burden velocity, and gas pressure are obtained through the ML model, which then inform a discontinuum model to predict far-field muckpile formation. The approach captures essential blast physics while significantly accelerating blast design optimization.